{"id":"W2996402632","doi":"10.1096/fj.201902143r","title":"Improving natural product research translation: From source to clinical trial","year":2019,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"National Center for Complementary and Integrative Health; National Institute on Aging; National Institutes of Health","keywords":"Transparency (behavior); Prioritization; Bridging (networking); Clinical trial; Computer science; Medicine; External validity; Risk analysis (engineering); Data science; Management science; Psychology; Pathology; Engineering; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001552588,0.0001002341,0.0001244938,0.00004367358,0.0002311774,0.0001179488,0.0003575777,0.00007651777,0.0000942523],"category_scores_gemma":[0.0003098672,0.00007187586,0.0001663862,0.00008757163,0.00008528037,0.000005878596,0.00007545833,0.0004199285,0.00008012453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001290539,"about_ca_system_score_gemma":0.000208268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002205246,"about_ca_topic_score_gemma":0.00001462784,"domain_scores_codex":[0.9983116,0.0004527855,0.0003282797,0.0002954566,0.0003299549,0.0002819388],"domain_scores_gemma":[0.9990246,0.00007824686,0.00007589313,0.0004143273,0.0002067385,0.0002002239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.02084863,0.000192861,0.004444035,0.00000907677,0.00007832766,0.000004946534,0.0001936179,0.00006574643,0.9235469,0.000005363861,0.008051113,0.04255934],"study_design_scores_gemma":[0.08505459,0.005696116,0.01513686,0.0001063299,0.0001841133,0.0001409595,0.001571341,0.0006234485,0.7079471,0.001522397,0.1810217,0.0009949941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935581,0.002474249,0.0005492125,0.001285879,0.001476373,0.0004603465,0.0000156118,0.000006181251,0.000174038],"genre_scores_gemma":[0.990319,0.0001220438,0.0007019046,0.000357309,0.007391846,0.000007055275,0.00003869982,0.00001772123,0.001044457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2155998,"threshold_uncertainty_score":0.2931013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06857704964745294,"score_gpt":0.3736920910828513,"score_spread":0.3051150414353984,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}